Please provide the following information when requesting support.
• Hardware RTX3090
• Network Type Segformer FAN
• TLT Version
tao info --verbose
Configuration of the TAO Toolkit Instance
task_group:
model:
dockers:
nvidia/tao/tao-toolkit:
5.0.0-tf2.11.0:
docker_registry: nvcr.io
tasks:
1. classification_tf2
2. efficientdet_tf2
5.0.0-tf1.15.5:
docker_registry: nvcr.io
tasks:
1. bpnet
2. classification_tf1
3. converter
4. detectnet_v2
5. dssd
6. efficientdet_tf1
7. faster_rcnn
8. fpenet
9. lprnet
10. mask_rcnn
11. multitask_classification
12. retinanet
13. ssd
14. unet
15. yolo_v3
16. yolo_v4
17. yolo_v4_tiny
5.2.0-pyt2.1.0:
docker_registry: nvcr.io
tasks:
1. action_recognition
2. centerpose
3. deformable_detr
4. dino
5. mal
6. ml_recog
7. ocdnet
8. ocrnet
9. optical_inspection
10. pointpillars
11. pose_classification
12. re_identification
13. visual_changenet
5.2.0.1-pyt1.14.0:
docker_registry: nvcr.io
tasks:
1. classification_pyt
2. segformer
dataset:
dockers:
nvidia/tao/tao-toolkit:
5.2.0-data-services:
docker_registry: nvcr.io
tasks:
1. augmentation
2. auto_label
3. annotations
4. analytics
deploy:
dockers:
nvidia/tao/tao-toolkit:
5.2.0-deploy:
docker_registry: nvcr.io
tasks:
1. visual_changenet
2. centerpose
3. classification_pyt
4. classification_tf1
5. classification_tf2
6. deformable_detr
7. detectnet_v2
8. dino
9. dssd
10. efficientdet_tf1
11. efficientdet_tf2
12. faster_rcnn
13. lprnet
14. mask_rcnn
15. ml_recog
16. multitask_classification
17. ocdnet
18. ocrnet
19. optical_inspection
20. retinanet
21. segformer
22. ssd
23. trtexec
24. unet
25. yolo_v3
26. yolo_v4
27. yolo_v4_tiny
format_version: 3.0
toolkit_version: 5.2.0.1
published_date: 01/16/2024
• Training spec file (added txt extension to be able to upload. yaml files not allowed) fan_train512X512.yaml.txt (2.6 KB)
• How to reproduce the issue?
I run
!tao model segformer train \
-e $SPECS_DIR/fan_train512X512.yaml \
-r $RESULTS_DIR/ \
-g $NUM_GPUS
And this is the complete run log torch.distributed.elastic.multiprocessing.api:failed.log (13.8 KB)
No clue what to do.
9 posts - 2 participants